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The Use of Information Theory in Epistemology

Published online by Cambridge University Press:  01 April 2022

William F. Harms*
Affiliation:
Department of Philosophy, Bowling Green State University

Abstract

Information theory offers a measure of “mutual information” which provides an appropriate measure of tracking efficiency for the naturalistic epistemologist. The statistical entropy on which it is based is arguably the best way of characterizing the uncertainty associated with the behavior of a system, and it is ontologically neutral. Though not appropriate for the naturalization of meaning, mutual information can serve as a measure of epistemic success independent of semantic maps and payoff structures. While not containing payoffs as terms, mutual information places both upper and lower bounds on payoffs. This constitutes a non-trivial relationship to utility.

Type
Research Article
Copyright
Copyright © Philosophy of Science Association 1998

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Footnotes

Send requests for reprints to the author, Department of Philosophy, Bowling Green State University, Bowling Green, OH 43403-0222.

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